Numerous studies illustrating the substantial potential for weather forecast improvements due to rapidly refreshed high spectral resolution infrared spectral sounding measurements have been conducted. In general, these benefits are the result of comparative measurements that show the development of unstable atmospheric conditions or that reveal motion of the atmosphere at different altitudes.
Recent analysis by members of the NASA Atmospheric Infrared Sounder (AIRS) AIRS Science Team shows that observations in the spectral range 1950-2450 cm−1 at AIRS' spectral resolution, result in vertical temperature profile retrieval accuracy in the lower troposphere nearly as good as that derived using the full AIRS spectral channel set. FIG. 1A shows Radiation Monitoring System (RMS) differences from European Centre for Medium Range Weather Forecasts (ECMWF) “truth” of Quality Controlled (QC'd) AIRS/AMSU (Advanced microwave sounding unit) temperature profile retrievals obtained when using all AIRS channels in the left side solid line and the left side dashed line, and when using all but 15 μm or 11 μm AIRS bands in the right side solid line and the right side dashed line. The results are shown using two QC procedures: Data Assimilation Quality Control (DAQC) which accepts fewer but more accurate retrievals; and Climate Quality Control (CQC), which accepts many more retrievals derived under more difficult cloud conditions. Results obtained using only mid-shortwave channels are somewhat degraded from those using all AIRS channels, but are still very good using either QC procedure.
However, there still exists a need for a higher spatial resolution system which would increase cloud contrast and result in further improved results using either DAQC or CQC procedure.
FIG. 1B shows improvements in GCM resolution compared to infrared and microwave observations over the past three decades. This trend line also indicates a need for models which can operate at a planned horizontal spatial resolution of 2-3 km within the next decade.
However, the Inventors have found that validation of a model of a given resolution must have observations as good as, or better than, the model itself, in order to minimize errors due to Nyquist (mathematical sampling theorem) spatial filtering processes in the models. Thus, there still exists a need for a higher spatial resolution system which would provide increased observation density in order to enable the data to better meet the information needs of the next generation of General Circulation Models (GCM). For example, cloud resolving models under development today should form the basis for the next generation of weather and climate models.